Update metadata.json

metadata.json

@@ -1,61 +1,140 @@
 {
-  "name": "MathVerse",
-  "release_date": "2024-03-22",
-  "subsets": {
-    "testmini": {
-      "language": [
-        "en"
-      ],
-      "modalities": [
-        "single_image_start"
-      ],
-      "task_type": "multiple_choice",
-      "score_type": "rule_llm_judge",
-      "score_protocol": {
-        "reference": "VLMEvalKit@vlmeval/dataset/utils/mathverse.py:123-167 — post_check_score exact-match prefetch, else GPT answer extraction (MathVerse_auxeval_extract) then GPT binary 0/1 correctness judgement (MathVerse_auxeval_score); same two-stage extract+score design as official ZrrSkywalker/MathVerse evaluation (extract_answer.py + score_answer.py). lmms-eval@lmms_eval/tasks/mathverse/mathverse_evals.py:92-110 judges every sample binary via LLM (quick_match optional exact match). [Re-verified in clone 2026-07-07: post_check_score at mathverse.py:126-133, auxeval_extract/score at 136-170; lmms score_answer at mathverse_evals.py:99-110.]",
-        "note": "Official protocol judges with an LLM after LLM extraction (binary 0/1); VLMEvalKit pre-resolves exact string matches by rule, which this classification adopts. mm-eval publishes the answer-only protocol (query_wo prompts, 'please directly answer'), not the official CoT eval (query_cot + multi-step CoT judging) — scores are comparable to VLMEvalKit MathVerse_MINI, not to the paper's CoT-E numbers. The HF repo also carries a testmini_text_only config (788 rows, no image) that metadata.json does not describe as a subset."
-      },
-      "prompt_template": "<image>{{ question }}",
-      "prompt_template_source": {
-        "origin": "source_column",
-        "reference": "https://huggingface.co/datasets/AI4Math/MathVerse (query_wo column = pre-rendered eval prompt)",
-        "notes": "Tier 2: MathVerse provides query_wo column which is the pre-rendered single-answer evaluation prompt produced by the official eval pipeline; we use it verbatim and prepend <image>."
-      },
-      "mapping_from_source": {
-        "media": {
-          "from": "image",
-          "type": "list",
-          "min_items": 1,
-          "max_items": 1
-        },
-        "id": {
-          "from": "sample_index"
-        },
-        "question": {
-          "from": "query_wo"
-        },
-        "answer": {
-          "from": "answer",
-          "optional": true
-        },
-        "extra": {
-          "question_type": {
-            "from": "question_type"
-          },
-          "problem_version": {
-            "from": "problem_version"
-          },
-          "problem_index": {
-            "from": "problem_index"
-          }
-        },
-        "source": {
-          "format": "huggingface",
-          "url": {
-            "testmini": "https://huggingface.co/datasets/AI4Math/MathVerse"
-          }
-        }
-      }
+ "name": "MathVerse",
+ "release_date": "2024-03-22",
+ "subsets": {
+  "testmini": {
+   "language": [
+    "en"
+   ],
+   "modalities": [
+    "single_image_start"
+   ],
+   "task_type": "multiple_choice_qa",
+   "score_type": "rule_llm_judge",
+   "score_protocol": {
+    "reference": "VLMEvalKit@vlmeval/dataset/utils/mathverse.py:123-167 — post_check_score exact-match prefetch, else GPT answer extraction (MathVerse_auxeval_extract) then GPT binary 0/1 correctness judgement (MathVerse_auxeval_score); same two-stage extract+score design as official ZrrSkywalker/MathVerse evaluation (extract_answer.py + score_answer.py). lmms-eval@lmms_eval/tasks/mathverse/mathverse_evals.py:92-110 judges every sample binary via LLM (quick_match optional exact match). [Re-verified in clone 2026-07-07: post_check_score at mathverse.py:126-133, auxeval_extract/score at 136-170; lmms score_answer at mathverse_evals.py:99-110.]",
+    "note": "Official protocol judges with an LLM after LLM extraction (binary 0/1); VLMEvalKit pre-resolves exact string matches by rule, which this classification adopts. mm-eval publishes the answer-only protocol (query_wo prompts, 'please directly answer'), not the official CoT eval (query_cot + multi-step CoT judging) — scores are comparable to VLMEvalKit MathVerse_MINI, not to the paper's CoT-E numbers. The HF repo also carries a testmini_text_only config (788 rows, no image) that metadata.json does not describe as a subset."
+   },
+   "prompt_template": "<image>{{ question }}",
+   "prompt_template_source": {
+    "origin": "source_column",
+    "reference": "https://huggingface.co/datasets/AI4Math/MathVerse (query_wo column = pre-rendered eval prompt)",
+    "notes": "Tier 2: MathVerse provides query_wo column which is the pre-rendered single-answer evaluation prompt produced by the official eval pipeline; we use it verbatim and prepend <image>."
+   },
+   "mapping_from_source": {
+    "media": {
+     "from": "image",
+     "type": "list",
+     "min_items": 1,
+     "max_items": 1
+    },
+    "id": {
+     "from": "sample_index"
+    },
+    "question": {
+     "from": "query_wo"
+    },
+    "answer": {
+     "from": "answer",
+     "optional": true
+    },
+    "extra": {
+     "question_type": {
+      "from": "question_type"
+     },
+     "problem_version": {
+      "from": "problem_version"
+     },
+     "problem_index": {
+      "from": "problem_index"
+     },
+     "source": {
+      "from": "source",
+      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+     },
+     "subfield": {
+      "from": "subfield",
+      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+     },
+     "subject": {
+      "from": "subject",
+      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+     }
+    },
+    "source": {
+     "format": "huggingface",
+     "url": {
+      "testmini": "https://huggingface.co/datasets/AI4Math/MathVerse"
+     }
     }
+   }
+  },
+  "testmini_text_only": {
+   "language": [
+    "en"
+   ],
+   "modalities": [
+    "text"
+   ],
+   "task_type": "multiple_choice_qa",
+   "score_type": "rule_llm_judge",
+   "score_protocol": {
+    "reference": "VLMEvalKit@vlmeval/dataset/utils/mathverse.py:123-167 — post_check_score exact-match prefetch, else GPT answer extraction (MathVerse_auxeval_extract) then GPT binary 0/1 correctness judgement (MathVerse_auxeval_score); same two-stage extract+score design as official ZrrSkywalker/MathVerse evaluation (extract_answer.py + score_answer.py). lmms-eval@lmms_eval/tasks/mathverse/mathverse_evals.py:92-110 judges every sample binary via LLM (quick_match optional exact match). [Re-verified in clone 2026-07-07: post_check_score at mathverse.py:126-133, auxeval_extract/score at 136-170; lmms score_answer at mathverse_evals.py:99-110.]",
+    "note": "Same protocol as the testmini subset (answer-only query_wo prompts, two-stage LLM extract+score). This subset IS the repo's testmini_text_only config (788 rows, text-dominant problems without the diagram image), previously published as data but undescribed in metadata.json; declared as a subset at the format-v3 re-emission."
+   },
+   "prompt_template": "{{ question }}",
+   "prompt_template_source": {
+    "origin": "source_column",
+    "reference": "https://huggingface.co/datasets/AI4Math/MathVerse (query_wo column = pre-rendered eval prompt)",
+    "notes": "Tier 2: MathVerse provides query_wo column which is the pre-rendered single-answer evaluation prompt produced by the official eval pipeline; we use it verbatim. Text-only variant rows carry no media, so no <image> placeholder is prepended."
+   },
+   "mapping_from_source": {
+    "media": {
+     "from": "image",
+     "type": "list",
+     "min_items": 0,
+     "max_items": 0
+    },
+    "id": {
+     "from": "sample_index"
+    },
+    "question": {
+     "from": "query_wo"
+    },
+    "answer": {
+     "from": "answer",
+     "optional": true
+    },
+    "extra": {
+     "question_type": {
+      "from": "question_type"
+     },
+     "problem_version": {
+      "from": "problem_version"
+     },
+     "problem_index": {
+      "from": "problem_index"
+     },
+     "source": {
+      "from": "source",
+      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+     },
+     "subfield": {
+      "from": "subfield",
+      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+     },
+     "subject": {
+      "from": "subject",
+      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+     }
+    },
+    "source": {
+     "format": "huggingface",
+     "url": {
+      "testmini_text_only": "https://huggingface.co/datasets/AI4Math/MathVerse"
+     }
+    }
+   }
   }
-}
+ }
+}